NVIDIA

NVIDIA

Posted via Workday

AI and ML Power Methodology Engineer

Posted Aug 5, 2026

Role at a glance

Salary
$136K – $264.5K/yr
Location
Santa Clara, California, United States
Work arrangement
On-site
Employment
Full-time
Experience
5+ years of experience.
Education
MS (or equivalent experience) with proven experience or PhD in related fields.

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Role Summary

AI-generated

The role develops AI/ML methodologies, tools, and data pipelines to estimate pre-silicon power and improve energy efficiency in NVIDIA GPUs and future AI solutions. Working with hardware, machine learning, and infrastructure experts, the position applies generative AI to power analysis, debugging, optimization, and chip design.

What You'll Do

  • Research, develop and own advanced AI/ML/DL methodologies to estimate pre-silicon power and improve GPU energy efficiency.
  • Develop tools for gathering, building, and annotating domain-specific datasets to train LLMs.
  • Develop tools for training and fine-tuning large language models, advanced RAG pipelines, vector databases, and agentic frameworks.
  • Build efficient data pipelines to gather power data from silicon and emulation sources.
  • Design LLM tools to analyze power patterns, generate optimized code, and provide actionable insights for power debugging and optimization.
  • Develop user-friendly data visualizations to simplify data analysis and insight generation.

Generated from the employer's posting. Verify important details before applying.

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Qualifications

Python and C++ rapid prototyping; data structures, algorithms, and software engineering; large language model training and fine-tuning; RAG pipelines, vector databases, and agentic frameworks; algorithm analysis including runtime and memory complexity; verbal and written English and interpersonal skills.

Required

  • Proficiency in rapid prototyping using languages like Python and C++
  • Strong foundational knowledge of data structures, algorithms, and software engineering principles
  • Familiarity with training and fine-tuning large language models, advanced Retrieval-Augmented Generation (RAG) pipelines, vector...
  • Ability to formulate and analyze algorithms, and comment on their runtime and memory complexities
  • Good verbal/written English and interpersonal skills

Original job description

Content provided by the employer

At NVIDIA, we pride ourselves in having energy-efficient products. We believe that continuing to maintain our products' energy efficiency compared to the competition is key to our continued success. Our team researches and develops methods to make NVIDIA's products more energy efficient. We develop and implement methodologies that leverage innovative AI advancements to enhance Nvidia's power team capabilities.

As an essential part of our Power Team, you'll closely collaborate with HW/ML experts and infrastructure teams. You'll work together to create new and improved ways to fix and improve power for NVIDIA's future AI solutions. Your contributions will help us understand energy usage in graphics and AI workloads and make improvements in architecture, design, and power management.

What you'll be doing:

  • Research, develop and own advanced AI/ML/DL methodologies to estimate pre-silicon power and improve GPU energy efficiency.

  • Develop tools that will help in the gathering, building, and annotation of domain specific datasets to train LLMs for different tasks, tools, and applications.

  • Make a difference by leveraging Gen AI technologies to solve complex problems in chip design, driving innovation and meaningful impact across the Power team.

  • Develop tools for training and fine-tuning large language models, advanced Retrieval-Augmented Generation (RAG) pipelines, vector databases and agentic frameworks.

  • Build efficient data pipelines to gather power data from different sources, such as silicon, emulation, for developing advanced data-dependent methodologies.

  • Design tools using LLMs to analyze power patterns, generate optimized code, and provide actionable insights for power debugging and optimization.

  • Enable efficient storage and retrieval of data from databases.

  • Develop user-friendly data visualizations to simplify data analysis and insight generation.

What we need to see:

  • MS (or equivalent experience) with proven experience or PhD in related fields.

  • 5+ years of experience.

  • Proficiency in rapid prototyping using languages like Python and C++, with strong foundational knowledge of data structures, algorithms, and software engineering principles.

  • Familiarity with training and fine-tuning large language models, advanced Retrieval-Augmented Generation (RAG) pipelines, vector databases and agentic frameworks.

  • Ability to formulate and analyze algorithms, and comment on their runtime and memory complexities.

  • Desire to bring quantitative decision-making and analytics to improve the energy efficiency of our products.

  • Good verbal/written English and interpersonal skills.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 136,000 USD - 218,500 USD for Level 3, and 168,000 USD - 264,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 21, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA

About the company

NVIDIA

Large Enterprise

NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.